September 2006


29 Sep 2006 12:32 am

[There is a updated version of this post: Top Ranked Blogs: April 2007.]

Turtle smallWelcome to the third edition of the Top Ranked Web Analytics blogs.

The evolution of the ranking system continues with a couple of tweaks to the ranking this time around. The primary determinant of the rank in the list below is still Technorati (click here).

To be considered the blog should primarily be on the topic of Web Analytics (50% or greater number of posts), as judged by a qualitative review (by me) of the last two months of posts.

Important: If you feel your blog has a higher Technorati ranking than 46k and it is not here please email me (blog at kaushik dot net). Especially if you are a non-English blog. Please contact me.

I was amazed at the change in the rankings each month (from June to July to this one). I did not expect so much flux in the rankings. Overall it is so fantastic that the number of blogs on the topic of web analytics continues to increase, as do the rankings of each blog. Viva la web analytics!!! 

Technorati
Rank Blog Sept July First Blog
Post
1 Hitwise Intelligence
by Bill Tancer
1,154 N/A N/A
2 E-Consultancy Internet Marketing Blog
by Ashley Friedlein
3,995 N/A N/A
3 Google Analytics Blog
by Jeff Gills
5,005 N/A 06/01/06
4 Occam's Razor
by Avinash Kaushik
6,591 20,124 05/14/06
5 Web Metrics Guru
by Marshall Sponder
7,126 8,086 02/09/06
6 Web Analytics World
by Manoj Jasra
35,315 N/A 05/18/06
7 Unofficial Google Analytics Blog
by Michael Harrison
36,319 61,923 12/30/05
8 Eric T. Peterson's Analytics Weblog
by Eric Peterson
36,838 91,240 05/01/04
9 Increasing your website's conversion rate
by Robbin Steif
43,761 76,223 10/22/05
10 Inside Web Analytics
by Matt Belkin
46,027 N/A 08/16/05

Some personal observations:

  • observationAny blog you see with a N/A in the July column was not on the list in July (and now they have the top three spots !).
  • Hitwise inclusion was a tough one because they are not “typical web analytics”, atleast most people don’t think so. In my mind Competitive Analysis is very much a cornerstone of any solid web analytics programs (Business case: click here & Usage: click here).
  • I am glad to see international representation continues with the E-consultancy blog.
  • Standards work. In the first list there was correct critique that not everyone will use, or have claimed a blog on, Technorati. This list proves that if you go out and suggest a standard people will figure out how to get on the standard. (And I thank you all for that.)
  • Competition is really tough in the blogosphere (hence gains of web analytics blogs are even more impressive). In mid-July it would have taken a blogger roughly 190 unique blog links to get a sub-10,000 technorati ranking. As of today a blogger would need approximately 230 unique blog links. Amazing.
  • You would have needed 58 unique blog links to make it to the list above today.

A Personal Best Blogs Ranking:

Here is my personal ranking of the “best” web analytics blogs (using the criteria that they “Eat like a bird, and poop like an elephant”). They get the ORbAK Stamp of Thanks! (and maybe a golden star to put on their blog : )).

    # 1: This Just In – Justin Cutroni
    (I am amazed at how much Justin contributes to the community, soon he will work himself out of a job because rather than hiring him I’ll just use his blog to fix every problem I have!! : )

    # 2: Increasing your website's conversion rate – Robbin Steif
    (The irrepressible Ms. Steif’s blog has a wealth of practical knowledge for any web analytics practitioner. Her honesty is to die for. : ))

    # 3: Commerce 360 Blog – Craig Danuloff
    (Craig shares a very unique real world perspective that I find very refreshing. He is frank, he adds a lot of value and his personality shines through clearly.)  

If you don’t have them on your RSS reader then I highly recommend them.

I’ll repeat the six “reporting tips” that I have collated in the process of doing these rankings: 

  1. Global standards and benchmarks are great because people buy into them more easily
  2. Simplicity always wins over complexity, because what people understand better they are more likely to action
  3. Judgment should be applied with a lot of careful consideration because reasonable people might disagree with someone they don’t know
  4. In any report context is king, provide the right context
  5. Be aware of hidden agendas, your’s and those of others
  6. Be open and up front with your assumptions
  7. Solicit feedback from your report consumers and incorporate relevant feedback in future iterations

So what do you think? How else can the ranking or the criteria be improved? Please share your feedback via comments.

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25 Sep 2006 01:26 am

DSCF3469 smallAs you can imagine choosing a web analytics tool is a critical process because whether you choose right or wrong you will be usually stuck with it for a while. Also because we tend to overstate the importance of historical web data (a post coming on this one of these days) it is quite likely that a quickie divorce will not be in the offing.

So in a world where choosing a web analytics tools seems akin to choosing a wife / husband / significant other, this blog post offers a radically different recommendation on how to choose your mate, sorry web analytics tool.

Summary: The current process of choosing a web analytics tool is fundamentally flawed. Why not change the process to: Implement Free Tool -> Learn -> Upgrade Analytics Skills -> Fix Data Capture -> Evaluate -> Now Choose?

The way tools are chosen at the moment is through a extensive process that usually looks like this:

  1. styleProcess smallCollect all the business requirements (goals, strategy, KPI's, reports, reporting schedule and so on)
  2. Collect all the technical requirements (site architecture, servers, scripts, pages, IT needs and so on)
  3. Ensure that anyone who could ever need any kind of access to any kind of web data is contacted (inside and outside the company) and their needs documented
  4. Put all of above into a RFP (Request for Proposal), and add vendor financial stability, references, etc into the requirements
  5. Send to vendors, set a very aggressive reply schedule
  6. Receive RFP’s
  7. From those weed out the “insignificants”
  8. Selection of one vendor that meets the requirements by a esteemed committee
  9. Implement (champagne celebration included)

The search process takes two to four months, implementation one to two, and there is one guaranteed result of this process eight times out of ten: You will pick the most expansive, and usually one of three expensive, vendor.

Roughly the same number of times you would have made a sub-optimal choice and you are looking into three, six, twelve months of stress and having to deal with management questions that sound like this: “how come you are using a quarter million dollars a year web analytics tool and you are not recommending actions”.

The achilles heel of the above process is that the process involved people who asked for the earth and moon in the requirements (most of whom will never even log into the tool) and it was very divorced from the rough and tumble real world of the web, website and web analytics.

The process is too long, too time consuming, the process itself is expensive (just count the people, process, and time commitments from your company) and you’ll always pick the most expensive and Rx smallexpansive tool.

As a antidote to this sub optimal outcome here is a recommendation: 1) Ignore the nine step process above and 2) Don’t do a RFP.

Here is a radical alternative that will set you on a path to finding your right soul-mate (I mean web analytics tool), and do so faster and cheaper:

Step 0: Assign optimal ownership. (Day One)

  • Project lead should be the person whose neck will be on the line to deliver web insights (not reports), for this post this person is you!
  • Provide him/her with a small group of one to two people who will put the tool to hard-core use.
  • Email the entire company (only slight exaggeration) to let them know you are selecting the tool.

Step 1: Implement a web analytics solution. (Day Two)

It takes one hour to get your hands on any of these tools. Five minutes to implement GA (tag into site footer, hit save, go get a drink and wait for data). Couple hours to implement CT, most of which will be you locating your website log files.

[Going out on a limb the recommendation is to stick to a javascript tag based solution because in the end it is quite likely that that most solutions use it so you might as well take a plunge now. That would be GA or StatCounter above.]

Step 2: Start using simple reports and process of creating a intelligent audience in your company. (Day Three)

  • Email your core users (whose job 100% depends on the website, so very few) a report that shows: Traffic (Visitors), Referring URL’s, Search Key Phrases, Top Viewed Pages
  • After a week set up a in person meeting to get feedback and questions
  • Create second revision of reports
  • After a week ask for feedback, in person, go to step 3 (because the feedback will tell you that the reports are not enough, show wrong stuff, they want more! : ))

In three days you went from nothing to actually having real data flow into your company and you are getting smarter by the second.

Step 3: Teach yourself the limitations of web analytics, tagging, numbers not matching, need to go redo your website IA / URL’s / ID’s / Cookies / data providing facilities. (Day 17)

  • skydiver smallBy now you have found that the reason you can’t answer questions is not the fault of your web analytics tool.
  • Make a list of all the problems (you’ll need someone with slight technical skills if you don’t have them), they’ll usually be: URL structures, missing data (need for new url parameters of cookie values), maybe updated javascript tags, etc.
  • Prioritize the problems (you plus your core team)

Step 4: IT “rules”! Cross your fingers, dive in. (Day 27)

  • Partner with your IT / Website Tech team to roll out the fixes you need to get your website to cough up data
  • This is often a painful process, cash in any chips you have (borrow some if you have to!)
  • Don’t forget to keep your reporting going and enhance as new data becomes available
  • Slowly increase your circle of data users

(Step 4 can take a lot of or little time depending on the size and mindset of your company. I am going to optimistically say this will take a month, YMMV.)

Step 5: Do a honest and deeply critical self review of where you are. (Day 57 or infinity)

self 20reviewAfter two months is your challenge probably is:

  • That you have no idea what to do with the data?
  • That you find that you don't know how to use the tool?
  • That the tool does not provide you with what you want?
  • That web analytics simply sucks?
  • That nobody buys anything the tools is telling you?

In five steps you have accomplished the impossible: You actually have a lot of in-depth knowledge of the tool (Google Analytics, ClickTracks or StatCounter), you have data flowing into your company and you are fixing things on your website that would have caused problems for any tool (and you are doing this without a single cent going to your web analytics vendor).

Remember even with time in step 4 you have have moved further faster than in the standard nine step process.

What you do next depends on the output of your Self Review (step 5). My guess on where you’ll be:

  • You’ll find out that reporting does not equal analysis and that you need a major upgrade in terms of the web analytics skills in your company [20%]
  • You’ll find that data or tool are not your problem, it really is your company culture (both in terms of using data or getting your site tech teams to do things to give you data) [20%]
  • You’ll find that Google Analytics or ClickTracks completely fill all your company web analytics needs [20%]
  • You’ll find that ClickTracks or Google Analytics are not the right web analytics tools for your company [20%]
  • You’ll realize that Web Analytics (clickstream data) is not sufficient to find web insights so you’ll take the money you would spend on web analytics vendors and spend it on Experience / Research analysis (see Trinity) [20%]

If the limitation is truly the tool then now you are ready for intelligent choice for a tough and practical selection process. My recommendations (whenever you are ready to chose a tool):

  • Your RFP should now contain the specific and actual problems are are having with the limitations of your current tool (Google Analytics, ClickTracks). And it should only be about the tool. No vendor can come give you a warm hug and solve your problems with your inability to capture data or have people to do analysis. Those are your problems to solve. [UPDATE: For more on how to craft a optimal Request for Proposal (RFP) strategy click here.]
  • 389913 reading glasses smallSelect differentiated vendors
    • Remember the Big Three are pretty much the same in functionality you need (except in 1% of features that niche businesses will value), so if your final list is the Big Three then you might miss out on a real differentiated choice. 
    • If you want a real comparison bring in a vendor that is radically different. So consider CoreMetrics, Visual Sciences (not HBX), Instadia, IndexTools, NetInsight, ClickTracks Pro etc, each of whom, IMHO, have something significantly different to put on the table.

  • Do a real Proof of Concept (implement the final set of vendors on your live site and compare with the free tool you were using to see if there is real differentiation).

So why should you do what some random blogger is recommending? If you follow the five step alternative process suggested above you’ll benefit from the following outcomes:

  • 590658 my freand smallYou were not paying through your nose, ears, eyes, etc to first fix the problems you had in your company. (Data capture, basic intelligence up-leveling etc.) If you pick a expensive and expansive vendor you are paying them to simply identify that you have problems, you have the option of doing that for free (and since the process of fixing your problems is months it is a nice chunk of change).
  • You have created atleast a core group of people who know what Web Analytics is everything that is frustrating and joyous about it:
    • IT: They learn that it is trivial to implement a web analytics tool. Javascript tag, copy, paste, save, done.
    • Web Site Developers: They learn all the little things that go into providing data that is business critical for actionability. Parameters to be added to url’s, page names to be updated, duplicated links in pages to be “lid’ed” so you can track them etc etc etc.
    • Report Creators: They’ll learn that web analytics is less about report writing and more about analysis and this list might be handy for them to evolve to the next level.
    • Web Analysts: They’ll learn that that they can use any tool to find a answer because they are Analysts. And of course that they have ultimate job security and we love them so.
    • Marketers: Magic does not exist. Forethought has to be put into doing campaigns and coordination with web site developers and analyst before launch so that things can be tracked after launch. And no the web analytics tool will not make them coffee each day nor give them a massage.
    • Business Leaders: Do a true assess of if they have the right skills in their folks, major gaps in their processes and that the true cost of web analytics not tools, it is the people (see the 10/90 rule).

  • You will have chosen the best tool for your company, with your eyes open and you would have upgraded your company’s Analytics sophistication in the process.
  • You will be promoted to VP of something as a reward and now have new worries to deal with.  [There is a very very small chance that you would have been so frustrated that you are ready to quit!!]

Ok now your turn. What do you think? Is this truly a radical alternative? Could you, or I, ever pull this off? Would you change something about this approach? Please share your feedback via comments.

[Like this post? For more posts like this please click here.]

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